基于百度大数据的信用舆情指数构建与实证研究

Construction and Empirical Study of Public Opinion Index on Credit Based on the Big-data of Baidu

提出基于大数据的信用舆情监测指数,以实现信用舆情的跨领域、跨区域、多维度动态监测。通过改进选词方法和指数合成模型,将695个信用相关百度关键词,按照不同领域、不同维度分类加权合成舆情指数。研究发现,2011年至2018年全社会各领域对信用的关注度普遍提高,信用舆情持续升温;不同阶段、不同领域、不同区域、多个维度不同程度呈现结构性信用舆情特征。研究认为,基于百度大数据的信用舆情指数,能够及时捕捉并准确揭示各个领域信用舆情的变化特征,客观反映社会整体信用舆情态势,具有较好的应用价值。

Monitoring public opinion index on credit based on big-data is put forward to achieve cross-field,cross-regional and multi-dimensional dynamic monitoring of public opinion on credit. By improving the method of word-selection and the index synthesis model, 695 credit-related key words of Baidu are classified and weighted according to their fields and dimensions, and synthesized into public opinion index. The study finds:the attention of all fields of the society to credit from the year 2011 to 2018 has generally increased and public opinion on credit continually heated up. The characteristic of structural public opinion on credit is displayed in different phases, different regions and multi-dimensions to different degree. The study argues that the public opinion index on credit based on the big-data of Baidu is able to timely capture and accurately demonstrate the changes of public opinion on credit of all fields, and objectively reflect the overall scenario of public opinion on credit of the society, which is of relatively good application value.